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Uptake and retention in clinical care for pre-exposure prophylaxis (PrEP) is suboptimal, particularly among young African American men who have sex with men (MSM) in the Deep South. We conducted a two-phase study to develop and implement an intervention to increase PrEP persistence. In Phase I, we conducted focus groups with 27 young African American MSM taking PrEP at a community health center in Jackson, Mississippi to elicit recommendations for the PrEP persistence intervention. We developed an intervention based on recommendations in Phase I, and in Phase II, ten participants were enrolled in an open pilot. Eight participants completed Phase II study activities, including a single intervention session, phone call check-ins, and four assessments (Months 0, 1, 3, and 6). Exit interviews demonstrated a high level of acceptability and satisfaction with the intervention. These formative data demonstrate the initial promise of a novel intervention to improve PrEP persistence among young African American MSM. [ABSTRACT FROM AUTHOR]

Background: Drug overdose persists as a leading cause of death in the United States, but resources to address it remain limited. As a result, health authorities must consider where to allocate scarce resources within their jurisdictions. Machine learning offers a strategy to identify areas with increased future overdose risk to proactively allocate overdose prevention resources. This modeling study is embedded in a randomized trial to measure the effect of proactive resource allocation on statewide overdose rates in Rhode Island (RI). Methods: We used statewide data from RI from 2016 to 2020 to develop an ensemble machine learning model predicting neighborhoodlevel fatal overdose risk. Our ensemble model integrated gradient boosting machine and super learner base models in a moving window framework to make predictions in 6-month intervals. Our performance target, developed a priori with the RI Department of Health, was to identify the 20% of RI neighborhoods containing at least 40% of statewide overdose deaths, including at least one neighborhood per municipality. The model was validated after trial launch. Results: Our model selected priority neighborhoods capturing 40.2% of statewide overdose deaths during the test periods and 44.1% of statewide overdose deaths during validation periods. Our ensemble outperformed the base models during the test periods and performed comparably to the best-performing base model during the validation periods. Conclusions: We demonstrated the capacity for machine learning models to predict neighborhood-level fatal overdose risk to a degree of accuracy suitable for practitioners. Jurisdictions may consider predictive modeling as a tool to guide allocation of scarce resources. [ABSTRACT FROM AUTHOR]

The study evaluated the acceptability of text message- and voice-based ecological momentary assessment (EMA) methods among a sample (N = 74) of young men who have sex with men (MSM). We assessed the acceptability of text message- and voice-based EMA methods. Almost all participants (96%) reported that they would be willing to accept texts on their smartphone to answer questions about their current mood, surroundings, or feelings. A large majority (89%) also reported being willing to accept phone calls to answer these questions. This work suggests that different EMA methods are acceptable for use among young MSM.

BackgroundLesbian, gay, bisexual, transgender, and queer (LGBTQ) community centers remain important venues for reaching and providing crucial health and social services to LGBTQ individuals in the United States. These organizations commonly use Facebook to reach their target audiences, but little is known about factors associated with user engagement with their social media presence. ObjectiveThis study aimed to identify factors associated with engagement with Facebook content generated by LGBTQ community centers in the United States. MethodsContent generated by LGBTQ community centers in 2017 was downloaded using Facebook’s application programming interface. Posts were classified by their content and sentiment. Correlates of user engagement were identified using negative binomial regression. ResultsA total of 32,014 posts from 175 community centers were collected. Posts with photos (incidence rate ratio, [IRR] 1.07; 95% CI 1.06-1.09) and videos (IRR 1.54; 95% CI 1.52-1.56) that contained a direct invitation for engagement (IRR 1.03; 95% CI 1.02-1.04), that expressed a positive sentiment (IRR 1.11; 95% CI 1.10-1.12), and that contained content related to stigma (IRR 1.16; 95% CI 1.14-1.17), mental health (IRR 1.33; 95% CI 1.31-1.35), and politics (IRR 1.28; 95% CI 1.27-1.29) received higher levels of engagement. ConclusionsThe results of this study provide support for the use of Facebook to extend the reach of LGBTQ community centers and highlight multiple factors that can be leveraged to optimize engagement.

Prior applications of machine learning to population health have relied on conventional model assessment criteria, limiting the utility of models as decision support tools for public health practitioners. To facilitate practitioners' use of machine learning as a decision support tool for area-level intervention, we developed and applied 4 practice-based predictive model evaluation criteria (implementation capacity, preventive potential, health equity, and jurisdictional practicalities). We used a case study of overdose prevention in Rhode Island to illustrate how these criteria could inform public health practice and health equity promotion. We used Rhode Island overdose mortality records from January 2016–June 2020 (n  = 1,408) and neighborhood-level US Census data. We employed 2 disparate machine learning models, Gaussian process and random forest, to illustrate the comparative utility of our criteria to guide interventions. Our models predicted 7.5%–36.4% of overdose deaths during the test period, illustrating the preventive potential of overdose interventions assuming 5%–20% statewide implementation capacities for neighborhood-level resource deployment. We describe the health equity implications of use of predictive modeling to guide interventions along the lines of urbanicity, racial/ethnic composition, and poverty. We then discuss considerations to complement predictive model evaluation criteria and inform the prevention and mitigation of spatially dynamic public health problems across the breadth of practice. This article is part of a Special Collection on Mental Health. [ABSTRACT FROM AUTHOR]

BackgroundUnderstanding where and how young black men who have sex with men (YBMSM) in the southern United States meet their sexual partners is germane to understanding the underlying factors contributing to the ongoing HIV transmission in this community. Men who have sex with men (MSM) commonly use geosocial networking apps to meet sexual partners. However, there is a lack of literature exploring geosocial networking app use in this particular population. ObjectiveOur aim was to examine the characteristics, preferences, and behaviors of a geographically diverse sample of geosocial networking app-using YBMSM in the southern United States. MethodsData were collected from a sample of 75 YBMSM across three cities (Gulfport, Mississippi; Jackson, Mississippi; and New Orleans, Louisiana). Multiple aspects of geosocial networking app use were assessed, including overall app use, age of participant at first app use, specific apps used, reasons for app use, photos presented on apps, logon times and duration, number of messages sent and received, and characteristics of and behaviors with partners met on apps. Survey measures of app-met partner and sexual behavior characteristics assessed at midpoint (Day 7) and completion visits (Day 14) were compared using McNemar’s test or Wilcoxon signed-rank test. In addition, we assessed activity spaces derived from GPS devices that participants wore for 2 weeks. ResultsOf the 70 participants who responded to the overall app-use item, almost three-quarters (53/70, 76%) had ever used geosocial networking apps. Jack’d was the most commonly used geosocial networking app (37/53, 70%), followed by Adam4Adam (22/53, 42%), and Grindr (19/53, 36%). The mean and median number of apps used were 4.3 (SD 2.7) and 4.0 (range 0-13), respectively. Most app-using participants displayed their face on the profile picture (35/52, 67%), whereas fewer displayed their bare legs (2/52, 4%) or bare buttocks (or ass; 2/52, 4%). The mean age at the initiation of app use was 20.1 years (SD 2.78) ranging from 13-26 years. Two-thirds (35/53, 66%) of the sample reported using the apps to “kill time” when bored. A minority (9/53, 17%) reported using the apps to meet people to have sex/hook up with. The vast majority of participants reported meeting black partners for sex. Over two-thirds (36/53, 68%) reported that the HIV status of their app-met partners was negative, and 26% (14/53) reported that they did not know their partner’s HIV status. There was a significant difference in GPS activity spaces between app using YBMSM compared to nonapp using YBMSM (2719.54 km2 vs 1855.68 km2, P=.011). ConclusionsUse of geosocial networking apps to meet sexual partners among our sample of YBMSM in the southern United States was common, with a diverse range of app use behaviors being reported. Further research should characterize the association between geosocial networking app use and engagement in sexual behaviors that increase risk for HIV acquisition and transmission. In addition, geosocial networking apps present a promising platform for HIV prevention interventions targeting YBMSM who use these apps.

BackgroundMany men who have sex with men (MSM) use apps to connect with and meet other MSM. Given that these apps are often used to arrange sexual encounters, it is possible that apps may be suitable venues for messages and initiatives related to HIV prevention such as those to increase HIV testing rates among this population. ObjectiveThe purpose of this study was to assess willingness to use a new app for reminders of when to be tested for HIV infection among a sample of MSM in London who use apps to arrange sexual encounters. MethodsBroadcast advertisements targeted users of a popular social-networking app for MSM in London. Advertisements directed users to a Web-based survey of sexual behaviors and sexual health needs. Willingness to use apps for reminders of when to be tested for HIV was assessed. In addition, participants responded to items assessing recent sexual behaviors, substance use, and demographic characteristics. Exploratory analyses were undertaken to examine differences in willingness to use an app by demographic and behavioral characteristics. ResultsBroadcast advertisements yielded a sample of 169 HIV-negative MSM. Overall, two-thirds (108/169, 63.9%) reported willingness to use an app to remind them when to be tested for HIV. There were no significant differences in willingness to use these apps based on demographic characteristics, but MSM who reported recent binge drinking and recent club drug use more frequently reported willingness to use this app compared to their nonusing counterparts. ConclusionsMSM in this sample are willing to use a new app for HIV testing reminders. Given the high levels of willingness to use them, these types of apps should be developed, evaluated, and made available for this population.

Background In light of the accelerating and rapidly evolving overdose crisis in the United States (US), new strategies are needed to address the epidemic and to efficiently engage and retain individuals in care for opioid use disorder (OUD). Moreover, there is an increasing need for novel approaches to using health data to identify gaps in the cascade of care for persons with OUD. Methods and findings Between June 2018 and May 2019, we engaged a diverse stakeholder group (including directors of statewide health and social service agencies) to develop a statewide, patient-centered cascade of care for OUD for Rhode Island, a small state in New England, a region highly impacted by the opioid crisis. Through an iterative process, we modified the cascade of care defined by Williams et al. for use in Rhode Island using key national survey data and statewide health claims datasets to create a cross-sectional summary of 5 stages in the cascade. Approximately 47,000 Rhode Islanders (5.2%) were estimated to be at risk for OUD (stage 0) in 2016. At the same time, 26,000 Rhode Islanders had a medical claim related to an OUD diagnosis, accounting for 55% of the population at risk (stage 1); 27% of the stage 0 population, 12,700 people, showed evidence of initiation of medication for OUD (MOUD, stage 2), and 18%, or 8,300 people, had evidence of retention on MOUD (stage 3). Imputation from a national survey estimated that 4,200 Rhode Islanders were in recovery from OUD as of 2016, representing 9% of the total population at risk. Limitations included use of self-report data to arrive at estimates of the number of individuals at risk for OUD and using a national estimate to identify the number of individuals in recovery due to a lack of available state data sources. Conclusions Our findings indicate that cross-sectional summaries of the cascade of care for OUD can be used as a health policy tool to identify gaps in care, inform data-driven policy decisions, set benchmarks for quality, and improve health outcomes for persons with OUD. There exists a significant opportunity to increase engagement prior to the initiation of OUD treatment (i.e., identification of OUD symptoms via routine screening or acute presentation) and improve retention and remission from OUD symptoms through improved community-supported processes of recovery. To do this more precisely, states should work to systematically collect data to populate their own cascade of care as a health policy tool to enhance system-level interventions and maximize engagement in care., Author(s): Jesse L. Yedinak 1, William C. Goedel 1, Kimberly Paull 2, Rebecca Lebeau 2, Maxwell S. Krieger 1, Cheyenne Thompson 2, Ashley L. Buchanan 3, Tom Coderre 4, Rebecca [...]

BackgroundGeosocial-networking apps like Grindr have been used increasingly among men who have sex with men (MSM) to meet anonymous partners. These mobile dating apps employ global positioning system technology to facilitate connections with other users based on their current location. These new technologies have generated quicker and easier modes for men who have sex with men to meet potential partners based on attraction and physical proximity. ObjectiveThe aim of this study is to describe geosocial-networking app use and recent sexual behaviors of MSM in the Atlanta metropolitan statistical area. MethodsOur sample was recruited from Grindr, the most commonly used of these mobile apps among MSM, using broadcast advertising. Advertisements were displayed over the course of a 72-hour period and participants were directed to a Web-based survey. ResultsIn total, 604 men clicked through the advertisement, and 92 users completed the survey. One-third (38.0%) of the men reported using these mobile apps to meet new sexual partners, and one-fifth (18.5%) used them to “kill time” when bored. Men reporting currently being in a relationship were less likely to report using these mobile apps to meet other MSM to date or to find a boyfriend or romantic partner, but more likely to report using these mobile apps to meet other MSM to have sex, X224=12.1, P=.016. Respondents had current accounts on 3.11 mobile apps (SD 1.84) on average, with Grindr being the most common (100%), followed by Scruff (52.5%), and Jack’d (45.7%). Most men were most active in the late night (40.2%), and on weekdays (64.1%). Each day, on average, men reported opening these mobile apps 8.38 times (SD 8.10) and spent 1.31 hours (SD 1.15) on these mobile apps. The age respondents began using these mobile apps was associated with the age at their first instance of insertive anal sex (r80=.527, P